基于全矢频带能量谱的风电机组齿轮箱故障诊断方法研究

针对风电机组齿轮箱局部微弱故障难于诊断的问题,提出全矢频带能量谱故障诊断方法。采用全矢理论对同源信号进行信息融合,获得相位不变、信息更完善的全矢信号,利用FIR滤波器对全矢信号进行分解,计算各频带能量作为识别工作状态的特征向量。分析风电机组齿轮箱的正常、齿根裂纹及均匀磨损信号的各频带能量,发现转频和啮合频率处的频带能量变化率能准确判别各类故障。通过对不同工况下50组信号的识别,证明该方法可有效区分风电机组齿轮箱的早期局部微弱故障。     

改进变分模态分解与去干扰包络因子的轴承故障分析

滚动轴承早期故障特征微弱且提取困难,考虑转频对故障包络信号的影响,提出改进包络谱特征因子(EDF),基于EDF提出优化变分模态分解方法(OVMD)。对滚动轴承正常、内圈及外圈状态进行OVMD分解,以EDF最大值作为筛选标准提取有效故障分量进行包络分析。结果表明:OVMD分解带有冲击分量信号,具有较高准确性,分解分量与原分量具有95%以上相似度;通过EDF最大值对分解分量进行提取,所获分量具有明显故障特征,并可排除转频对故障特征频的干扰;采用OVMD-EDF故障提取方法,并进行包络分析,可对不同故障程度的内圈、外圈故障进行精准故障诊断。     

基于自适应变分模态分解及多重分形谱的风力机轴承故障分析

风力机齿轮箱轴承故障信号具有典型非线性及非平稳特性,采用自适应变分模态法对4种状态下振动信号进行分解,提出基于分形盒维数-峭度阈值法(Adaptived Variational Mode Decomposition,AVMD)对处理所得分量进行筛选,选取富含故障信息的分量进行信号重构,采用多重分形去趋势波分析方法,分析重构信号的分形特征并识别其工作状态,结果表明:基于多重分形去趋势波分析法对非稳定轴承可进行有效地故障识别;轴承振动信号具有典型分形特征,在不同时间尺度下,标度指数、广义Hurst指数与多重分形谱均可反应轴承工作状态;3种多重分形谱参数对故障类型敏感度不同,谱函数最大值对应的奇异指数对内圈故障较为敏感,峰值占比对外圈故障较为敏感,分形谱宽对滚珠故障较为敏感。     

改进小波包联合PNN的风电故障诊断研究

针对风电机组故障信号的非平稳性以及故障与征兆的非线性映射导致的故障识别困难问题,提出了改进型的节点重构小波包频带能量谱与PNN(概率神经网络)的联合故障诊断新方法。文章深入分析了传统小波包频带错乱的问题,借助傅里叶变换与傅里叶逆变换改进了小波包,消除了小波包频带错乱的缺陷。首次采用改进型小波包提取故障信号特征量作为PNN的输入,然后利用PNN快速准确的非线性映射能力进行故障诊断。最后,采用风力发电机故障试验台的故障轴承的实际数据对所提方法进行验证,结果表明,所提方法可行且有效。     

基于AVMD和WDK的风电齿轮箱轴承复合故障诊断方法研究

针对强背景噪声下轴承微弱复合故障特征提取困难的问题,提出一种基于自适应变分模态分解（AVMD）和优化的Wasserstein距离指标（WDK）的风电齿轮箱轴承复合故障诊断方法。首先,引入自适应学习粒子群优化算法（ALPSO）,以平均包络熵作为ALPSO的适应度函数来搜索变分模态分解的最佳影响参数,从而构造AVMD;其次,结合Wasserstein距离（WD）和峭度优点,提出WDK指标筛选有效模态分量,并对筛选的有效模态分量进行重构;然后,通过对重构信号进行包络谱分析实现轴承复合故障的诊断;最后,将所提AVMD-WDK方法应用于某风场2 MW风电齿轮箱轴承振动信号的故障诊断。结果表明,该方法能有效提取轴承的微弱故障特征,实现轴承复合故障的精确诊断。     

风电机组滚动轴承复合故障诊断研究

针对在强风电机组背景噪声下进行滚动轴承复合故障诊断时,由于故障之间的相互联系、交叉影响使得多种故障特征混叠在一起,易造成漏诊、误判等问题,提出一种基于多点最优调整的最小熵解卷积(multipoint optimal minimum entropy deconvolution adjusted,MOMEDA)与1.5维能量谱相结合的风电机组滚动轴承复合故障诊断方法;首先利用MOMEDA算法对原始滚动轴承振动信号进行解卷积预处理;然后对解卷积信号进行1.5维能量谱分析;最后通过分析谱图中幅值突出的频率成分来判断故障类型。仿真信号和应用实例分析结果表明,该方法能够有效提取出在强背景噪声下的复合故障特征,实现风电机组轴承复合故障的准确诊断。     

基于NLMS-WP及BP的风机轴承故障诊断方法

为解决风机轴承故障诊断问题,全面提取轴承运行状态的特征信息,提出了基于NLMS与WP相融合的特征提取及神经网络相适配的故障诊断方法。首先采用自适应滤波器对故障信号进行滤波去噪,再利用小波包对信号进行分解重构并提取其能量特征,将小波包各个频段的能量比系数作为风机轴承的故障特征,并通过改进的神经网络模型分类识别轴承的故障信号,实现不同类型的轴承故障诊断。试验结果表明,该方法弥补了传统故障诊断方法的不足,提高了故障类型识别率和故障诊断准确率,诊断效果良好。     

一种W型结构元素的自适应数学形态学及其在风电机组轴承故障诊断中应用

为了提高风电机组滚动轴承故障诊断的有效性和可靠性,提出一种W型自适应数学形态学特征提取方法,并与谱相关分析相结合形成风电机组滚动轴承故障诊断策略。该方法首先针对传统三角型结构元素在故障特征提取中易出现对脉冲信号的漏查,提出一种W型结构元素,旨在捕捉更多特征信息;之后依据各故障信号的实际波形得到结构元素的高和最优开闭运算加权因子,构建自适应形态学模型;最后对测试信号与训练信号进行频域内谱相关性分析,依据相关系数识别故障。将该方法通过数值例、西储大学实验台轴承数据和实际风场采集数据进行算法验证,并与传统的三角型结构元素进行比较,实验结果表明W型结构元素能更有效地提取信号中的脉冲成分、降低噪声干扰,故障诊断算法可准确识别出故障类别,提高结果的可靠性。     

小波神经理论在风力机齿轮箱故障诊断系统中的应用

风力机齿轮箱振动信号是一种时频特性复杂的非平稳信号,常规的时域和频域分析方法难以有效的分析齿轮箱故障及提取故障特征。提出一种基于小波分析和神经网络的风力机齿轮箱故障诊断方法,该方法采用小波时频分析技术对风力发电机故障振动信号进行消噪滤波,通过小波包分解系数求取频带能量,根据各个频带能量的变化提取故障特征,为实现智能诊断提供故障特征值。应用BP神经网络进行故障识别,并采用LabVIEW和matlab软件予以实现。结果表明,该方法能有效提高风力发电机组齿轮箱故障诊断的准确性。     

基于阶比跟踪及共振解调的连杆轴承故障诊断研究

针对发动机连杆轴承磨损故障诊断中测取的机体振动信号非平稳、频率成分及故障机理复杂的特点,提出了基于阶比跟踪及共振解调的诊断方法。在加速工况下,分别将第3缸连杆轴承间隙调节为0.07、0.20和0.40mm,采集机体振动信号,结合同步采集的转速信号及第1缸外卡油压信号对振动信号的时频分布进行分析,发现振动信号在0.90～1.25kHz频带存在明显的冲击成分,其相位近似分布在第3缸燃爆相位附近,其幅值与连杆磨损程度成正比。在加速状态下对上述冲击成分包络解调及阶比跟踪后提取参数发现,连杆轴承正常、轻微及严重磨损工况的参数分别分布在0.48、1.00和2.50V附近,提取的参数能有效区分出这些工况。     

Ash-forming elements in four Scandinavian wood species. Part 1: Summer harvest

Woody biomass in Finland and Sweden comprises mainly four wood species: spruce, pine, birch and aspen. To study the ash, which may cause problems for the combustion device, one tree of each species were cut down and prepared for comparisons with fuel samples. Well-defined samples of wood, bark and foliage were analyzed on 11 ash-forming elements: Si, Al, Fe, Ca, Mg, Mn, Na, K, P, S and Cl. The ash content in the wood tissues (0.2–0.7%) was low compared to the ash content in the bark tissues (1.9–6.4%) and the foliage (2.4–7.7%). The woods’ content of ash-forming elements was consequently low; the highest contents were of Ca (410–1340 ppm) and K (200–1310), followed by Mg (70–290), Mn (15–240) and P (0–350). Present in the wood was also Si (50–190), S (50–200) and Cl (30–110). The bark tissues showed much higher element contents; Ca (4800–19,100 ppm) and K (1600–6400) were the dominating elements, followed by Mg (210–2400), P (210–1200), Mn (110–1100) and S (310–750), but the Cl contents (40–330) were only moderately higher in the bark than in the wood. The young foliage (shoots and deciduous leaves) had the highest K (7100–25,000 ppm), P (1600–5300) and S (1100–2600) contents of all tissues, while the shoots of spruce had the highest Cl contents (820–1360) and its needles the highest Si content (5000–11,300). This paper presented a new approach in fuel characterization: the method excludes the presence of impurities, and focus on different categories of plant tissues. This made it possible to discuss the contents of ash element in a wide spectrum of fuel-types, which are of large importance for the energy production in Finland and Sweden.     

Contents in Volume 23,2014

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Performance assessment of some ice TES systems

In this paper, a performance assessment of four main types of ice storage techniques for space cooling purposes, namely ice slurry systems, ice-on-coil systems (both internal and external melt), and encapsulated ice systems is conducted. A detailed analysis, coupled with a case study based on the literature data, follows. The ice making techniques are compared on the basis of energy and exergy performance criteria including charging, discharging and storage efficiencies, which make up the ice storage and retrieval process. Losses due to heat leakage and irreversibilities from entropy generation are included. A vapor-compression refrigeration cycle with R134a as the working fluid provides the cooling load, while the analysis is performed in both a full storage and partial storage process, with comparisons between these two. In the case of full storage, the energy efficiencies associated with the charging and discharging processes are well over 98% in all cases, while the exergy efficiencies ranged from 46% to 76% for the charging cycle and 18% to 24% for the discharging cycle. For the partial storage systems, all energy and exergy efficiencies were slightly less than that for full storage, due to the increasing effect wall heat leakage has on the decreased storage volume and load. The results show that energy analyses alone do not provide much useful insight into system behavior, since the vast majority of losses in all processes are a result of entropy generation which results from system irreversibilities.     

NEXT GENERATION ENGINEERED MATERIALS FOR ULTRA SUPERCRITICAL STEAM TURBINES

正1 ABSTRACT To reduce the effect of global warming on our climate,the levels of CO2emissions should be reduced.One way to do this is to increase the efficiency of electricity production from fossil fuels.This will in turn reduce the amount of CO2emissions for a given power output.Using US practice for efficiency calculations,then a move from a typical US plant running at 37%efficiency to a 760℃/38.5 MPa(1 400/5 580 psi)plant running at 48%efficiency would reduce CO2emissions by 170kg/MW.hr or 25%.     

Effect of co-cultivation of Chlamydomonas reinhardtii with Azotobacter chroococcum on hydrogen production

Chlamydomonas reinhardtii cc124 and Azotobacter chroococcum bacteria were co-cultured with a series of volume ratios and under a variety of light densities to determine the optimal culture conditions and to investigate the mechanism by which co-cultivation improves H₂ yield. The results demonstrated that the optimal culture conditions for the highest H₂ production of the combined system were a 1:40 vol ratio of bacterial cultures to algal cultures under 200 μE m^?2 s^?1. Under these conditions, the maximal H₂ yield was 255 μmol mg^?1 Chl, which was approximately 15.9-fold of the control. The reasons for the improvement in H₂ yield included decreased O₂ content, enhanced algal growth, and increased H₂ase activity and starch content of the combined system.     

Aerodynamic performance effects of leading-edge geometry in gas-turbine blades

The purpose of this paper is to illustrate the advantages of the direct surface-curvature distribution blade-design method, originally proposed by Korakianitis, for the leading-edge design of turbine blades, and by extension for other types of airfoil shapes. The leading edge shape is critical in the blade design process, and it is quite difficult to completely control with inverse, semi-inverse or other direct-design methods. The blade-design method is briefly reviewed, and then the effort is concentrated on smoothly blending the leading edge shape (circle or ellipse, etc.) with the main part of the blade surface, in a manner that avoids leading-edge flow-disturbance and flow-separation regions. Specifically in the leading edge region we return to the second-order (parabolic) construction line coupled with a revised smoothing equation between the leading-edge shape and the main part of the blade. The Hodson–Dominy blade has been used as an example to show the ability of this blade-design method to remove leading-edge separation bubbles in gas turbine blades and other airfoil shapes that have very sharp changes in curvature near the leading edge. An additional gas turbine blade example has been used to illustrate the ability of this method to design leading edge shapes that avoid leading-edge separation bubbles at off-design conditions. This gas turbine blade example has inlet flow angle 0°, outlet flow angle −64.3°, and tangential lift coefficient 1.045, in a region of parameters where the leading edge shape is critical for the overall blade performance. Computed results at incidences of −10°,   −5°,   +5°,   +10° are used to illustrate the complete removal of leading edge flow-disturbance regions, thus minimizing the possibility of leading-edge separation bubbles, while concurrently minimizing the stagnation pressure drop from inlet to outlet. These results using two difficult example cases of leading edge geometries illustrate the superiority and utility of this blade-design method when compared with other direct or inverse blade-design methods.     

Exergetic evaluation of 5 biowastes-to-biofuels routes via gasification

This paper presents the exergy analysis results for the production of several biofuels, i.e., SNG (synthetic natural gas), methanol, Fischer–Tropsch fuels, hydrogen, as well as heat and electricity, from several biowastes generated in the Dutch province of Friesland, selected as one of the typical European regions. Biowastes have been classified in 5 virtual streams according to their ultimate and proximate analysis. All production chains have been modeled in Aspen Plus in order to analyze their technical performance. The common steps for all the production chains are: pre-treatment, gasification, gas cleaning, water–gas-shift reactions, catalytic reactors, final gas separation and upgrading. Optionally a gas turbine and steam turbines are used to produce heat and electricity from unconverted gas and heat removal, respectively. The results show that, in terms of mass conversion, methanol production seems to be the most efficient process for all the biowastes. SNG synthesis is preferred when exergetic efficiency is the objective parameter, but hydrogen process is more efficient when the performance is analyzed by means of the 1st Law of Thermodynamics. The main exergy losses account for the gasification section, except in the electricity and heat production chain, where the combined cycle is less efficient.     

Natural-gas fueled spark-ignition (SI) and compression-ignition (CI) engine performance and emissions

Natural gas is a fossil fuel that has been used and investigated extensively for use in spark-ignition (SI) and compression-ignition (CI) engines. Compared with conventional gasoline engines, SI engines using natural gas can run at higher compression ratios, thus producing higher thermal efficiencies but also increased nitrogen oxide (NO_x) emissions, while producing lower emissions of carbon dioxide (CO₂), unburned hydrocarbons (HC) and carbon monoxide (CO). These engines also produce relatively less power than gasoline-fueled engines because of the convergence of one or more of three factors: a reduction in volumetric efficiency due to natural-gas injection in the intake manifold; the lower stoichiometric fuel/air ratio of natural gas compared to gasoline; and the lower equivalence ratio at which these engines may be run in order to reduce NO_x emissions. High NO_x emissions, especially at high loads, reduce with exhaust gas recirculation (EGR). However, EGR rates above a maximum value result in misfire and erratic engine operation. Hydrogen gas addition increases this EGR threshold significantly. In addition, hydrogen increases the flame speed of the natural gas-hydrogen mixture. Power levels can be increased with supercharging or turbocharging and intercooling. Natural gas is used to power CI engines via the dual-fuel mode, where a high-cetane fuel is injected along with the natural gas in order to provide a source of ignition for the charge. Thermal efficiency levels compared with normal diesel-fueled CI-engine operation are generally maintained with dual-fuel operation, and smoke levels are reduced significantly. At the same time, lower NO_x and CO₂ emissions, as well as higher HC and CO emissions compared with normal CI-engine operation at low and intermediate loads are recorded. These trends are caused by the low charge temperature and increased ignition delay, resulting in low combustion temperatures. Another factor is insufficient penetration and distribution of the pilot fuel in the charge, resulting in a lack of ignition centers. EGR admission at low and intermediate loads increases combustion temperatures, lowering unburned HC and CO emissions. Larger pilot fuel quantities at these load levels and hydrogen gas addition can also help increase combustion efficiency. Power output is lower at certain conditions than diesel-fueled engines, for reasons similar to those affecting power output of SI engines. In both cases the power output can be maintained with direct injection. Overall, natural gas can be used in both engine types; however further refinement and optimization of engines and fuel-injection systems is needed.     

Controls on the Karaha–Telaga Bodas geothermal reservoir,Indonesia

Karaha–Telaga Bodas is a partially vapor-dominated, fracture-controlled geothermal system located adjacent to Galunggung Volcano in western Java, Indonesia. The geothermal system consists of: (1) a caprock, ranging from several hundred to 1600 m in thickness, and characterized by a steep, conductive temperature gradient and low permeability; (2) an underlying vapor-dominated zone that extends below sea level; and (3) a deep liquid-dominated zone with measured temperatures up to 353 °C. Heat is provided by a tabular granodiorite stock encountered at about 3 km depth. A structural analysis of the geothermal system shows that the effective base of the reservoir is controlled either by the boundary between brittle and ductile deformational regimes or by the closure and collapse of fractures within volcanic rocks located above the brittle/ductile transition. The base of the caprock is determined by the distribution of initially low-permeability lithologies above the reservoir; the extent of pervasive clay alteration that has significantly reduced primary rock permeabilities; the distribution of secondary minerals deposited by descending waters; and, locally, by a downward change from a strike-slip to an extensional stress regime. Fluid-producing zones are controlled by both matrix and fracture permeabilities. High matrix permeabilities are associated with lacustrine, pyroclastic, and epiclastic deposits. Productive fractures are those showing the greatest tendency to slip and dilate under the present-day stress conditions. Although the reservoir appears to be in pressure communication across its length, fluid, and gas chemistries vary laterally, suggesting the presence of isolated convection cells.     

Hydrogen production by steam-gasification of carbonaceous materials using concentrated solar energy – V. Reactor modeling,optimization, and scale-up

A chemical reactor for the steam-gasification of carbonaceous particles (e.g. coal, coke) is considered for using concentrated solar radiation as the energy source of high-temperature process heat. A two-phase reactor model that couples radiative, convective, and conductive heat transfer to the chemical kinetics is applied to optimize the reactor geometrical configuration and operational parameters (feedstock's initial particle size, feeding rates, and solar power input) for maximum reaction extent and solar-to-chemical energy conversion efficiency of a 5 kW prototype reactor and its scale-up to 300 kW. For the 300 kW reactor, complete reaction extent is predicted for an initial feedstock particle size up to 35 μm at residence times of less than 10 s and peak temperatures of 1818 K, yielding high-quality syngas with a calorific content that has been solar-upgraded by 19% over that of the petcoke gasified.